To manage a thermal environment of a structure such as a residential or commercial building, one or more HVAC control systems are typically used. HVAC control systems need to make decisions as to how to condition the enclosure appropriately, which may include varying an internal heat, humidity, or other environmental characteristic. Since the enclosure has an associated thermal mass that needs to be heated or cooled, how and when the heating or cooling is carried out can greatly impact the energy efficiency as well as the cost of the process.
Conventionally, a model that attempts to specify how a structure will behave under the influence of an HVAC system is created based on a variety of factors such as structure size, number and characteristics of windows included in the structure, etc. That model is then used to specify the type and size of HVAC system to install and/or it is used by the HVAC control system throughout the lifetime of the building. For example, U.S. Pat. No. 7,072,727 discusses a method for determining heat loss of a building and for the proper sizing of HVAC equipment for the building.
It is also known for model updates to occur after installation through simple calculations such as adding heat and measuring time and temperature. For example, U.S. Pat. No. 5,555,927 discusses an adapted recovery method for a setback thermostat using the intersection of the space temperature with a sloped recovery temperature line which approximates the change in temperature as a function of time during recovery of the temperature controlled space from the setback temperature, to determine the time at which recovery to the occupancy temperature should begin. The recovery line slope is re-calculated and updated.
U.S. Patent Application Publication No. 2005/0192915 discusses a system for forecasting predicted thermal loads for a building including a neural-network-based thermal load predictor. The neural network can be trained using building data, occupancy data and actual weather conditions. A thermal condition forecaster uses a simple regression model based on forecasted high and low temperatures for a specific locale and measured local temperature and humidity observations made immediately prior to the prediction.
While such systems have evolved the technological field of HVAC control based on thermodynamic models of a structure, there remains significant room for improving the accuracy of the thermodynamic models in characterizing changes to a thermal environment of a structure over time as a result of actuation of an associated HVAC system.